The present invention relates to the electrical, electronic, and computer arts, and more specifically, to methods and systems for facilitating personalized down-time activities.
Several million users daily call to get a customer service (e.g., for banking service, revenue authority, utility companies, retailers, airlines agents, publishers, etc.). During such calls, most users experience periods of down-time in which they are not interacting with a customer service representative. Service providers implement tools to reduce down-time and improve customer experience, by monitoring the interactions of their customer throughout a service experience, e.g., to improve the quality of service, to understand various characteristics and factors of the customer (and customer agent) such as a perceived level of stress, frustration, etc. Such data can further be consumed by computer algorithms and intelligent applications (i) to infer customer experience, (dis)satisfaction level, sentiment, emotion, etc.; (ii) to infer customer service effectiveness; or (iii) to determine product recommendation, etc.